Update README.md

README.md

@@ -6,35 +6,24 @@ tags:
 datasets:
 - arcee-ai/sec-data-mini
 ---
+## Quick Summary
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
+This model is an adaptation of the `mistralai/Mistral-7B-Instruct-v0.2`, refined through the application of layer pruning techniques as detailed in the paper "The Unreasonable Ineffectiveness of the Deeper Layers." It incorporates methodologies from the `MergeKit` and `PruneMe` repositories to optimize its structure, focusing on reducing redundancy within the model's deeper layers without compromising its ability to generate coherent text. The model is maintained by Arcee-ai and represents a practical implementation of computational efficiency improvements in Large Language Models (LLMs), aiming to balance performance with resource usage effectively.
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** Arcee-ai
-- **Create from model :** mistralai/Mistral-7B-Instruct-v0.2
+This model represents a specialized iteration of the `mistralai/Mistral-7B-Instruct-v0.2`, optimized for efficiency and performance through selective layer pruning. Developed by Arcee-ai, it leverages insights from the "The Unreasonable Ineffectiveness of the Deeper Layers" research. The pruning process was informed by the `MergeKit` and `PruneMe` tools, focusing on eliminating redundant layers to ensure a leaner, more efficient model capable of generating high-quality text outputs.
 
 ### Model Sources
 
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [https://github.com/arcee-ai/PruneMe]
-- **Paper :** [https://arxiv.org/pdf/2403.17887.pdf]
+- **Pruning:** [PruneMe GitHub (unofficial)](https://github.com/arcee-ai/PruneMe)
+- **Paper:** ["The Unreasonable Ineffectiveness of the Deeper Layers"](https://arxiv.org/pdf/2403.17887.pdf)
+- **Merging Repository:** [MergeKit GitHub](https://github.com/arcee-ai/mergekit)
 
 ## Uses
 
-Some of the use cases - https://github.com/arcee-ai/PruneMe/tree/main?tab=readme-ov-file#use-cases
+This pruned model is designed for a range of NLP tasks, with a focus on maintaining or even enhancing the model's original capabilities in generating coherent text, despite the reduction in its size. It stands as a testament to the feasibility of layer pruning in preserving the essential functional attributes of a model while offering a template for computational resource optimization.
 
 ### Downstream Use
 
-Can be use to finetune. It would be nice to explore the continual pre-training as well.
+The pruned model serves as a robust foundation for fine-tuning on specific tasks and is an ideal candidate for exploring continuous pre-training opportunities. Its development is a direct application of principles outlined in "The Unreasonable Ineffectiveness of the Deeper Layers," utilizing the `MergeKit` and `PruneMe` repositories for practical pruning implementation. This model is a step forward in efficient model design, demonstrating the potential for significant reductions in computational resource requirements without detrimental effects on performance.